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Solutions Manual for Foundations of Mathematical Economics | Michael Carter | Complete Chapter Solutions

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This complete Solutions Manual for Foundations of Mathematical Economics by Michael Carter provides detailed, step-by-step solutions covering mathematical methods used in modern economics, including functions, linear algebra, matrix operations, differential and integral calculus, optimization techniques, comparative statics, constrained optimization, dynamic analysis, difference equations, probability, and economic modeling. The material reinforces theoretical concepts while demonstrating practical applications in microeconomics, macroeconomics, and quantitative economic analysis. Designed for economics, econometrics, finance, mathematics, business, MBA, and quantitative social science students, this solutions manual supports coursework review, assignment completion, examination preparation, and the development of analytical problem-solving skills using mathematical methods in economics. The content follows the official textbook organization and covers all major topics presented in the book.

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Solutions Manual
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Foundations of Mathematical Economics

Michael Carter
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November 15, 2002
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Trustedscholar

, c 2001 Michael Carter

Solutions for Foundations of Mathematical Economics All rights reserved




Chapter 1: Sets and Spaces

1.1
{ 1, 3, 5, 7 . . . } or { 𝑛 ∈ 𝑁 : 𝑛 is odd }
1.2 Every 𝑥 ∈ 𝐴 also belongs to 𝐵. Every 𝑥 ∈ 𝐵 also belongs to 𝐴. Hence 𝐴, 𝐵 have
precisely the same elements.
1.3 Examples of finite sets are
∙ the letters of the alphabet { A, B, C, . . . , Z }
∙ the set of consumers in an economy
∙ the set of goods in an economy
∙ the set of players in a game.
Examples of infinite sets are
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∙ the real numbers ℜ
∙ the natural numbers 𝔑
∙ the set of all possible colors
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∙ the set of possible prices of copper on the world market
∙ the set of possible temperatures of liquid water.
1.4 𝑆 = { 1, 2, 3, 4, 5, 6 }, 𝐸 = { 2, 4, 6 }.
1.5 The player set is 𝑁 = { Jenny, Chris }. Their action spaces are
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𝐴𝑖 = { Rock, Scissors, Paper } 𝑖 = Jenny, Chris
1.6 The set of players is 𝑁 = {1, 2, . . . , 𝑛 }. The strategy space of each player is the set
of feasible outputs
𝐴𝑖 = { 𝑞𝑖 ∈ ℜ+ : 𝑞𝑖 ≤ 𝑄𝑖 }
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where 𝑞𝑖 is the output of dam 𝑖.
1.7 The player set is 𝑁 = {1, 2, 3}. There are 23 = 8 coalitions, namely
𝒫(𝑁 ) = {∅, {1}, {2}, {3}, {1, 2}, {1, 3}, {2, 3}, {1, 2, 3}}
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There are 2 coalitions in a ten player game.
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1.8 Assume that 𝑥 ∈ (𝑆 ∪ 𝑇 )𝑐 . That is 𝑥 ∈ / 𝑆 ∪ 𝑇 . This implies 𝑥 ∈ / 𝑆 and 𝑥 ∈ / 𝑇,
or 𝑥 ∈ 𝑆 𝑐 and 𝑥 ∈ 𝑇 𝑐. Consequently, 𝑥 ∈ 𝑆 𝑐 ∩ 𝑇 𝑐 . Conversely, assume 𝑥 ∈ 𝑆 𝑐 ∩ 𝑇 𝑐 .
This implies that 𝑥 ∈ 𝑆 𝑐 and 𝑥 ∈ 𝑇 𝑐 . Consequently 𝑥 ∈ / 𝑆 and 𝑥 ∈ / 𝑇 and therefore
𝑥∈/ 𝑆 ∪ 𝑇 . This implies that 𝑥 ∈ (𝑆 ∪ 𝑇 )𝑐 . The other identity is proved similarly.
1.9

𝑆=𝑁
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𝑆∈𝒞

𝑆=∅
𝑆∈𝒞
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Trustedscholar

, c 2001 Michael Carter

Solutions for Foundations of Mathematical Economics All rights reserved


𝑥2
1




𝑥1
-1 0 1




-1

Figure 1.1: The relation { (𝑥, 𝑦) : 𝑥2 + 𝑦 2 = 1 }
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1.10 The sample space of a single coin toss is { 𝐻, 𝑇 }. The set of possible outcomes in
three tosses is the product
{
{𝐻, 𝑇 } × {𝐻, 𝑇 } × {𝐻, 𝑇 } = (𝐻, 𝐻, 𝐻), (𝐻, 𝐻, 𝑇 ), (𝐻, 𝑇, 𝐻),
}
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(𝐻, 𝑇, 𝑇 ), (𝑇, 𝐻, 𝐻), (𝑇, 𝐻, 𝑇 ), (𝑇, 𝑇, 𝐻), (𝑇, 𝑇, 𝑇 )


A typical outcome is the sequence (𝐻, 𝐻, 𝑇 ) of two heads followed by a tail.
1.11

𝑌 ∩ ℜ𝑛+ = {0}
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where 0 = (0, 0, . . . , 0) is the production plan using no inputs and producing no outputs.
To see this, first note that 0 is a feasible production plan. Therefore, 0 ∈ 𝑌 . Also,
0 ∈ ℜ𝑛+ and therefore 0 ∈ 𝑌 ∩ ℜ𝑛+ .
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To show that there is no other feasible production plan in ℜ𝑛+ , we assume the contrary.
That is, we assume there is some feasible production plan y ∈ ℜ𝑛+ ∖ {0}. This implies
the existence of a plan producing a positive output with no inputs. This technological
infeasible, so that 𝑦 ∈
/ 𝑌.
1.12 1. Let x ∈ 𝑉 (𝑦). This implies that (𝑦, −x) ∈ 𝑌 . Let x′ ≥ x. Then (𝑦, −x′ ) ≤
(𝑦, −x) and free disposability implies that (𝑦, −x′ ) ∈ 𝑌 . Therefore x′ ∈ 𝑉 (𝑦).
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2. Again assume x ∈ 𝑉 (𝑦). This implies that (𝑦, −x) ∈ 𝑌 . By free disposal,
(𝑦 ′ , −x) ∈ 𝑌 for every 𝑦 ′ ≤ 𝑦, which implies that x ∈ 𝑉 (𝑦 ′ ). 𝑉 (𝑦 ′ ) ⊇ 𝑉 (𝑦).
1.13 The domain of “<” is {1, 2} = 𝑋 and the range is {2, 3} ⫋ 𝑌 .
1.14 Figure 1.1.
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1.15 The relation “is strictly higher than” is transitive, antisymmetric and asymmetric.
It is not complete, reflexive or symmetric.
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Trustedscholar

, c 2001 Michael Carter

Solutions for Foundations of Mathematical Economics All rights reserved


1.16 The following table lists their respective properties.
< ≤
√ =

reflexive ×
√ √ √
transitive √ √
symmetric ×

asymmetric √ ×
√ ×

anti-symmetric √ √
complete ×
Note that the properties of symmetry and anti-symmetry are not mutually exclusive.
1.17 Let ∼ be an equivalence relation of a set 𝑋 ∕= ∅. That is, the relation ∼ is reflexive,
symmetric and transitive. We first show that every 𝑥 ∈ 𝑋 belongs to some equivalence
class. Let 𝑎 be any element in 𝑋 and let ∼ (𝑎) be the class of elements equivalent to
𝑎, that is
∼(𝑎) ≡ { 𝑥 ∈ 𝑋 : 𝑥 ∼ 𝑎 }
Since ∼ is reflexive, 𝑎 ∼ 𝑎 and so 𝑎 ∈ ∼(𝑎). Every 𝑎 ∈ 𝑋 belongs to some equivalence
class and therefore
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𝑋= ∼(𝑎)
𝑎∈𝑋

Next, we show that the equivalence classes are either disjoint or identical, that is
∼(𝑎) ∕= ∼(𝑏) if and only if f∼(𝑎) ∩ ∼(𝑏) = ∅.
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First, assume ∼(𝑎) ∩ ∼(𝑏) = ∅. Then 𝑎 ∈ ∼(𝑎) but 𝑎 ∈
/ ∼(𝑏). Therefore ∼(𝑎) ∕= ∼(𝑏).
Conversely, assume ∼(𝑎) ∩ ∼(𝑏) ∕= ∅ and let 𝑥 ∈ ∼(𝑎) ∩ ∼(𝑏). Then 𝑥 ∼ 𝑎 and by
symmetry 𝑎 ∼ 𝑥. Also 𝑥 ∼ 𝑏 and so by transitivity 𝑎 ∼ 𝑏. Let 𝑦 be any element
in ∼(𝑎) so that 𝑦 ∼ 𝑎. Again by transitivity 𝑦 ∼ 𝑏 and therefore 𝑦 ∈ ∼(𝑏). Hence
∼(𝑎) ⊆ ∼(𝑏). Similar reasoning implies that ∼(𝑏) ⊆ ∼(𝑎). Therefore ∼(𝑎) = ∼(𝑏).
We conclude that the equivalence classes partition 𝑋.
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1.18 The set of proper coalitions is not a partition of the set of players, since any player
can belong to more than one coalition. For example, player 1 belongs to the coalitions
{1}, {1, 2} and so on.
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1.19
𝑥 ≻ 𝑦 =⇒ 𝑥 ≿ 𝑦 and 𝑦 ∕≿ 𝑥
𝑦 ∼ 𝑧 =⇒ 𝑦 ≿ 𝑧 and 𝑧 ≿ 𝑦
Transitivity of ≿ implies 𝑥 ≿ 𝑧. We need to show that 𝑧 ∕≿ 𝑥. Assume otherwise, that
is assume 𝑧 ≿ 𝑥 This implies 𝑧 ∼ 𝑥 and by transitivity 𝑦 ∼ 𝑥. But this implies that
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𝑦 ≿ 𝑥 which contradicts the assumption that 𝑥 ≻ 𝑦. Therefore we conclude that 𝑧 ∕≿ 𝑥
and therefore 𝑥 ≻ 𝑧. The other result is proved in similar fashion.
1.20 asymmetric Assume 𝑥 ≻ 𝑦.
𝑥 ≻ 𝑦 =⇒ 𝑦 ∕≿ 𝑥
while
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𝑦 ≻ 𝑥 =⇒ 𝑦 ≿ 𝑥
Therefore
𝑥 ≻ 𝑦 =⇒ 𝑦 ∕≻ 𝑥
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